A random mix from the whole library. Shuffle for a new set.
A man wired his lab instruments to his home network, put all their manuals and programming guides into an AI project, and the AI wrote most of the first set of Python programs that control the instruments and pull data from them. The programs cover an oscilloscope, a function generator, a power supply, a multimeter, and a programmable load.
AI session of about 60 minutes produced narrated English and French video versions for his project for about 30 dollars at API rates, with reusable assets.
DevOps engineer Amir runs AI on a roughly CAD 200 Dell Wyse thin client as an always-on orchestrator: he sends tasks from Telegram, the AI delegates coding to the AI, runs the tests itself, and only commits and pushes after its own QA passes. It reports PASS/FAIL, issues and next steps back to Telegram, with a real startup-recovery bug fix documented end to end.
Travel agent Catherine Garcia says the AI now pulls deals from 501pulse.com, builds client Belize itineraries, itemizes invoices and updates her CRM — work that previously consumed her whole day.
Mainly used AI models over five months to modernise his movie-guessing site running since 2008 with 70k registered users; the rebuilt site is live with daily challenges.
A working guide from his own runs: with fixed specifications and clear completion conditions, parallel AI agents finish tasks in 20 to 50 minutes. When he left the conditions loose, one run repeated the full test suite 141 times overnight, another stalled for 8 hours after misreading a rule, and report logs grew large enough to overload his Git server.
Andrew Connell moved 426 pages, 281 course pages, 217 videos and 8,911 comments back to his own site after closing his Voitanos business, with every old URL answering with a single 301. The AI did most of the work over six months in his personal time, and his site went from about 5 percent of the organic search share to close to 90 percent in two months.
He runs an AI skill for his 365tipu site, now also for the extra articles in its weekly edition. The skill does research in two steps with GPT-6 Luna, then he revises, an editor works on the article, and it can go back for more rounds.
A builder runs AI as a night shift for his side project. Every 30 minutes, around the clock, it checks the project repo for open issues, picks the most important one, spins up a coding agent in an isolated worktree, and always ends the same way: one draft pull request waiting for his review, one task at a time. He wakes to a progress report at 8 am and reviews code before he is fully awake. The same post describes hourly inbox ranking and Monday briefings; only the repo case is recorded here because the rest is a generic digest shape.
He spent 4 weeks designing and testing an upgrade of their 16 node HPC cluster with AI, and the AI then did the full reinstall itself. The reinstall covered remote install, network booted images, Slurm setup, a shared filesystem, and web services that give their users a small cloud platform.
Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.